Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Other (Please Specify) In a relationship 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to jazz;Listen to rock/indie music;Listen to hiphop and rap;Listen to classical music;Go to gigs;Go to the opera;Exercise;Go to museums and galleries;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Smartwatch;Tablet 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Every day
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Solving math or logical problems;Generate art 
Contexts of LLM use: Personal;Technical;Learning;School/University;Work 
Prompt 1: How do I work out carbon emissions where there is no data
Prompt 2: What do I do if I'm in a relationship that is verbally and financially abusive?
Prompt 3: Will companies in the UK forgive the debt because of these reasons?
Prompt 4: What are other words for stink
Prompt 5: Weather in Preston, UK today
Prompt 6: please write a cover letter for a job application
Prompt 7: The job is for an environmental consultant
Prompt 8: Please write an email to get some experience and/or paid employment
Prompt 9: How to make myself stand out of job apps
Prompt 10: Customise this CV and cover letter for me please 
Comments: I take them with a grain of salt, I would never used them word for word and for scientific statements I would always check them with a peer reviewed source